AI for Summarization – Enabling Human-Consumable Information

In the first post in this series on Artificial Intelligence: Monster or Mentor? we saw that there are several key ways in which AI advances can improve human productivity in organizations. In this article, we’ll look at the first: Distillation.

Distillation is applying AI approaches to automate making large data volumes interpretable. Just like miners distill tons of raw ore into ounces of gold using machines, the goal is to automate the identification of value in big data. Here, we’ll focus specifically on how Distillation can be applied to the business problem of customer experience.

Companies interact with their customers in more and more ways, across ever-increasing numbers of service channels: call centers, web-chat, email, automated chat-bots, social media—the list goes on. A growing challenge is to understand your customer’s experience, even as they traverse this massive web of communications and interactions. Being able to distill answers to simple questions like the following can deliver enormous business value.

Why are they contacting us?

How can we most effectively interact in order to reduce service channel costs?

What can we do to make this a positive interaction?

Where/when should we intercede in the future to pre-empt the need for contacting us?

Roy Wilds leads the data science team at PHEMI Systems, and is responsible for designing and building data analytics and data science software to extract insights from data. Roy has served as data mining team lead for multiple research teams, and has helped build protection tools for various data mining operations. Prior to becoming the Chief Data Scientist at PHEMI, Roy was the Director of Product Management responsible for PHEMI Central™ product development and strategy.